Uncertain Context Information Research Articles

Inconsistency elimination of multi-source information fusion in smart home using the Dempster-Shafer evidence theory

In the smart home, inconsistencies in multi-source information often occur due to the vast quantities and diverse varieties of context information, and the Dempster-Shafer (D-S) evidence theory exhibits remarkable efficacy in addressing this issue. However, the use of basic possibility assignment (BPA) to quantify the credibility of information may introduce the uncertainty contained in the original data. In order to obtain a more reliable BPA and improve the accuracy of multi-source information fusion, an index that combines the relationships of sources and the information volume of context (RSIVC) is defined to comprehensively calculate the uncertainty of context information. In addition, interval distance is introduced to calculate the credibility of the proposition (CoP), which quantifies the correspondence among uncertain context information and all propositions in the frame of discernment (FoD). Finally, based on the d-S evidence theory, a multi-discount context information inconsistency elimination (MDCIE) algorithm using RSIVC and CoP is proposed, which is specifically applied to address the problem of inconsistency in multi-source light intensity information in smart homes. In the experimental part, we compare the traditional and state-of-the-art inconsistency elimination algorithms to verify the effectiveness of the proposed algorithm. Besides, we also test the efficiency of various components of the MDCIE algorithm as well as several RSIVC indicator-building strategies to ensure that the proposed algorithm is optimal. Under the conditions of high precision, medium precision, and low precision of sensors, the context-judge rate reaches 99.24 %, 98.58 %, and 98.09 %, respectively, which corroborates that the MDCIE algorithm is highly effective.

Situation‐awareness and reasoning using uncertain context in mobile peer‐to‐peer environments

PurposeThe recent advances of mobile computing and sensing technologies have enabled mobile devices to individually sense environment context and develop situation awareness capability. To gain a better understanding of the environment, mobile devices that are co‐located can establish a mobile peer‐to‐peer (MP2P) environment to share their individual context information. The purpose of this paper is to propose a theoretical model for representing and reasoning about situations using uncertain context information captured by multiple devices in an MP2P environment.Design/methodology/approachThe paper proposes a generic model for reasoning about situations using uncertain context information captured by multiple devices in a MP2P environment. A data fusion technique is then integrated into the proposed model. To deal with uncertainty of context information captured by multiple independent devices, several models to estimate reliability of context information captured in the environment is proposed and developed.FindingsThe proposed model has been implemented as a middleware and evaluated using data from real experiments in various scenarios and environment settings. The results of the experiments show the robust performances of the proposed model as the basis for situation reasoning in the environment.Originality/valueA novel model to represent situations and context information captured by multiple devices and to estimate reliability context information used for situation reasoning is proposed. The proposed model is then implemented as a middleware and validated using context data taken captured by multiple independent devices in a MP2P environment.

Design of hierarchical coordination model for ubiquitous application

Our research targets collaborative environments with focus on mobility and teams. This environment comprise a number of people working on multiple tasks and activities simultaneously. As mobile and wireless technology advances people are no longer bound to their offices. Team members are able to collaborate while on the move. So, mobile ubiquitous application can be a best solution to provide a mobility and collaboration for the environment. And the issue must be considered how to coordinate these ubiquitous application seamlessly and efficiently. We present a methodology for context modeling and employ a framework that reduces costs such as computing information and usage of network resources by transferring context at relevant levels of detail. At the same time, robustness of the system is improved by dealing with uncertain context information. Our framework is implemented on an OSGi container platform using Web services for communication means.